iTagPlot

iTagPlot computes and visualizes normalized tag density (read coverage) across targeted genomic regions to facilitate interpretation of capture-based sequencing data.

Key Features:

• Tag density calculation: Computes normalized read depth (tag density/read coverage) across targeted genomic regions.
• Parallel computation: Leverages multicores and grid engine technologies to compute tag density efficiently across functional features.
• Visualization: Produces visual representations of computed tag density to aid interpretation of genomic regions.
• Stratification and clustering: Enables stratification of features using summary statistics and unsupervised clustering methods.
• Functional grouping: Defines groups by biological function or measurement criteria to organize and compare complex datasets.

Scientific Applications:

• Capture-based sequencing analysis: Interprets normalized read depth from capture-based sequencing to reveal underlying biological phenomena.
• Comparative genomics: Supports comparative analyses by stratifying and visually summarizing tag density across feature groups.
• Functional genomics: Facilitates investigation of functional features by summarizing and clustering read coverage profiles.
• Epigenetics: Enables examination of tag density patterns relevant to epigenetic studies.

Methodology:

Normalization of read depth across targeted genomic regions; computation of tag density/read coverage across functional features; parallel computation using multicores and grid engine; stratification using summary statistics and unsupervised clustering; grouping by biological function or measurement criteria.